60 Atlantic Avenue, Toronto

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Four Steps to Success

1

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  • Scientific Framework: Define objectives, testable hypotheses, and methodology tracking
  • 14 Question Types: Single/multi-choice, Likert, NPS, image selection, ranking, and more
  • Virtuoso Branching: Complex AND/OR logic supporting 150+ question national surveys
  • Smart Sample Sizing: AI calculates optimal sample based on confidence intervals
  • Multilingual: 6 languages (en-US, en-GB, en-CA, en-AU, es-MX, es-ES)
  • Rehearsal Mode: Test questionnaires before field deployment

2

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  • Sampling Frames: Multi-layer stratification with cryptographic SHA-256 hashing
  • Blockchain-Style Manifests: Chain-linked audit trails with tamper-proof verification
  • Reproducible Sampling: Cryptographically secure random seeds for exact replication
  • Territory Management: Mapbox geofencing with GPS validation and risk assessment
  • ISO 20252 Compliant: Meets ESOMAR and AAPOR professional standards
  • 10-Year Retention: Cloud storage for regulatory compliance

3

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  • CAPI (Face-to-Face): AtlasSamplerโ„ข single-visit workflow with offline PWA and GPS validation
  • CAWI (Web): Opinion.Tips federation with RSA-signed schemas and fraud detection
  • CATI (Phone): Production-ready infrastructure with operator status and call disposition tracking
  • 66% Time Reduction: AtlasSamplerโ„ข completes listing + interview in one visit vs. traditional 3-day methods
  • Real-Time Monitoring: Live GPS tracking, quality scoring, and AI anomaly detection
  • Offline-First: Intelligent sync retry with exponential backoff for network interruptions

4

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  • RAG-Powered Analytics: Ask questions in natural language with Debriefer using Google Vertex AI
  • Triple-Hash Weighting: Post-stratification with raking and cell weighting algorithms
  • Semantic Search: pgvector-powered similarity search for contextual data retrieval
  • Source Citations: Every AI response includes document references for verification
  • Weighted Export: CSV, SPSS, Excel with cryptographic verification for compliance
  • Cost-Optimized: Target <$0.01 per query with smart model routing and Redis caching

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